Assembly line balancing: Joint precedence graphs under high product variety

Previous approaches for balancing mixed-model assembly lines rely on detailed forecasts of the demand for each model to be produced on the line (model mix). With the help of the anticipated model mix a joint precedence graph for a virtual average model is deduced, so that the mixed-model balancing problem is reduced to the single-model case and traditional balancing approaches can be employed. Today's ever increasing product variety often impedes reliable forecasts for individual models. Instead, forecasts for the estimated occurrences of each product feature (e.g., percentage of cars with air conditioning) are merely obtainable. This paper shows how the generation of joint precedence graphs can be altered to account for this fundamental change in information. For the first time a tractable approach to provide the information necessary to balance mixed-model assembly lines carrying considerable product variety is presented.